Cargando…

AgBase: a unified resource for functional analysis in agriculture

Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessibl...

Descripción completa

Detalles Bibliográficos
Autores principales: McCarthy, Fiona M., Bridges, Susan M., Wang, Nan, Magee, G. Bryce, Williams, W. Paul, Luthe, Dawn S., Burgess, Shane C.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1751552/
https://www.ncbi.nlm.nih.gov/pubmed/17135208
http://dx.doi.org/10.1093/nar/gkl936
_version_ 1782131430125469696
author McCarthy, Fiona M.
Bridges, Susan M.
Wang, Nan
Magee, G. Bryce
Williams, W. Paul
Luthe, Dawn S.
Burgess, Shane C.
author_facet McCarthy, Fiona M.
Bridges, Susan M.
Wang, Nan
Magee, G. Bryce
Williams, W. Paul
Luthe, Dawn S.
Burgess, Shane C.
author_sort McCarthy, Fiona M.
collection PubMed
description Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessible, public resource ‘AgBase’ (). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteogenomic mapping. Proteogenomic data are available from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The ‘GO Consortium’ gene association file contains the most rigorous GO annotations based solely on experimental data. The ‘Community’ gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted annotations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely available on request. A suite of tools for analyzing functional genomics datasets using the GO is available online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations.
format Text
id pubmed-1751552
institution National Center for Biotechnology Information
language English
publishDate 2007
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-17515522007-02-22 AgBase: a unified resource for functional analysis in agriculture McCarthy, Fiona M. Bridges, Susan M. Wang, Nan Magee, G. Bryce Williams, W. Paul Luthe, Dawn S. Burgess, Shane C. Nucleic Acids Res Articles Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessible, public resource ‘AgBase’ (). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteogenomic mapping. Proteogenomic data are available from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The ‘GO Consortium’ gene association file contains the most rigorous GO annotations based solely on experimental data. The ‘Community’ gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted annotations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely available on request. A suite of tools for analyzing functional genomics datasets using the GO is available online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations. Oxford University Press 2007-01 2006-11-29 /pmc/articles/PMC1751552/ /pubmed/17135208 http://dx.doi.org/10.1093/nar/gkl936 Text en © 2006 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
McCarthy, Fiona M.
Bridges, Susan M.
Wang, Nan
Magee, G. Bryce
Williams, W. Paul
Luthe, Dawn S.
Burgess, Shane C.
AgBase: a unified resource for functional analysis in agriculture
title AgBase: a unified resource for functional analysis in agriculture
title_full AgBase: a unified resource for functional analysis in agriculture
title_fullStr AgBase: a unified resource for functional analysis in agriculture
title_full_unstemmed AgBase: a unified resource for functional analysis in agriculture
title_short AgBase: a unified resource for functional analysis in agriculture
title_sort agbase: a unified resource for functional analysis in agriculture
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1751552/
https://www.ncbi.nlm.nih.gov/pubmed/17135208
http://dx.doi.org/10.1093/nar/gkl936
work_keys_str_mv AT mccarthyfionam agbaseaunifiedresourceforfunctionalanalysisinagriculture
AT bridgessusanm agbaseaunifiedresourceforfunctionalanalysisinagriculture
AT wangnan agbaseaunifiedresourceforfunctionalanalysisinagriculture
AT mageegbryce agbaseaunifiedresourceforfunctionalanalysisinagriculture
AT williamswpaul agbaseaunifiedresourceforfunctionalanalysisinagriculture
AT luthedawns agbaseaunifiedresourceforfunctionalanalysisinagriculture
AT burgessshanec agbaseaunifiedresourceforfunctionalanalysisinagriculture